Being good stopped being the same as being legible.
ModelVox exists because a layer has appeared between companies and their buyers that nobody is managing — and because the two industries best placed to manage it are both solving a different problem.
There is a sentence about your company you have never read. That is the whole reason we exist.
A new reader arrived, and it has strange habits.
For twenty years, being chosen meant being found and then being persuasive. Both happened on your own property: the buyer arrived, read your words, formed a view. You controlled the encounter.
That encounter now frequently does not happen. A model reads the market on the buyer's behalf and hands over a summary — one or two sentences about you, next to one or two about a competitor. Your website did not write those sentences. It was one input among many, and not the most trusted one, because nothing weights self-description highly.
This new reader has habits worth learning. It never asks a follow-up question. It discounts what you say about yourself. It rewards specificity it can verify somewhere else. And it produces a description whether or not you have given it good material — which means the choice is not whether to be described, only whether to be described well.
ModelVox is a positioning firm for a market where machines do the describing. We find the sentence AI systems produce about a company now, decide the one that should replace it, and build the evidence — on the site and off it — that makes the new one the easiest thing to say.
Evidence over assertion. It is the only line that matters.
There is no shortage of firms ready to produce more content, run more campaigns and add more tools. Volume is rarely the constraint. The constraint is a precise, defensible answer to why you matter — and the evidence that lets somebody else confirm it without asking you.
So we do not sell output. We take a small number of engagements, we tell clients when the claim they want is not yet true, and we decline work we do not think will pay for itself. That is not a virtue position. It is the only stance consistent with the argument we make, and a firm that argued for corroboration while selling assertion would be worth ignoring.
Evidence over assertion
A claim a model will repeat has to be corroborated, not merely stated. We build positions on what is demonstrably true and findable by someone who has never spoken to you.
Difference over volume
One sharp, defensible claim beats a library of generic content — and in this market, generic content actively makes the problem worse.
Order over enthusiasm
Legibility, then claim, then corroboration. Running that sequence backwards is the most common and most expensive mistake in the category.
Machines as an audience
AI systems are now a stakeholder in your market. How they describe you is part of your position, not a technical afterthought.
Precision about uncertainty
We separate what is documented from what is inference from what nobody knows. In a market full of confident invention, that separation is the product.
Willingness to decline
The engagements we turn down are the reason to trust the ones we take. If the evidence will not support the claim, the honest recommendation is to stop.
Taras Netrev
Founder, ModelVox
I have spent my career on the distance between what a technology is and what people understand it to be. I held a senior marketing role at Intel, and I have founded several software companies — including a product development firm with an R&D centre in Ukraine, working with venture-backed startups in Silicon Valley and established businesses in France. ModelVox exists because that distance has changed shape. The audience deciding what your company is now includes machines; they are reading everything said about you; and almost nobody is managing what they conclude.
What we have not done.
Everyone in this market has proof. A great deal of it is decorative — logos from a discovery call, metrics with no baseline, testimonials nobody can verify. Since our entire argument is that corroborated claims beat confident ones, listing proof we cannot substantiate would make the argument worthless. So here is the disclosure. It stays on the site, and it changes as the facts do.
As of August 2026
- No published client case studies. The work exists and the write-ups are with clients for approval. Nothing appears on this site with a client's name on it until they have read and approved every word — which is slower than the alternative and the only version worth anything.
- No awards, certifications, analyst placements or partner badges. We have not applied for any.
- No privileged access to any model provider. Nobody selling this service has it, including the firms implying otherwise.
- Our own AI visibility is early. This site was rebuilt against the method we sell. The corroboration layer takes months and we are at the start of it — which means you can watch whether the method works on us.
What we do have: a method we walk you through before you pay for anything, a complimentary first call that produces a finding you keep, and a record of telling people the work was not worth doing.
On the firm.
The questions worth asking before a first call.
When the question turns to reliability, we don't answer it ourselves.
We are accountable for how a market and its machines understand you. Whether your production agents actually work, and whether the code behind them would survive diligence, are different questions — and an independent finding is worth more than ours. Two separate firms with their own methods: one audits the agent, one audits the code. Neither sells the fix, which is exactly why their finding carries weight.
A five-day, fixed-price CARA Audit™ that scores a production agent 0–100 across task completion, consistency, tool use, safety, and evaluation — run like a penetration test, not a demo. You walk away with a ranked 90-day fix roadmap. Building that fix is someone else's job.
A Technical Integrity Audit™ that goes under the hood — architecture, technical debt, AI-generated code risk — the diligence investors and boards run before they bet on what you've built. Built for the moment your codebase becomes a deal term, not an afterthought.
Start with the finding.
Tell us the question in front of your leadership team. We come back with an honest read on whether we can help — and if we cannot, we will say who might.
The first call is complimentary — and the finding is yours to keep.
What you can actually hire us to do.
Positioning & Category Creation
Decide the sentence. Make it true. Make it only true of you.
AI Search Visibility Audit
Read the sentence models produce about you today — and where it came from.
Market & Opportunity Mapping
Find the market where demand is large and the recommendation is still unclaimed.
AI Marketing Intelligence
Separate the activity that fills dashboards from the influence that moves revenue.
AI Implementation & Operations
One workflow. A baseline before we build. A measured result in 30 days.
Marketing Evaluation & Reliability
AI scales content. It scales mistakes at the same speed.